Computer networks are known to be used to accumulate data about individuals, corporations, and other organizations. Such data can be in the form of user social connections, reviews and opinions about corporations and organizations, opinions about content, and similar. However, due to the nature of widely distributed computer networks, such as the Internet, the authenticity of such data is often suspect.
Data pertaining to social connections and interactions can lack authenticity for a wide variety of reasons. The technological workings of a computerized social network may allow users to express a quantitative opinion about information posted by other users (e.g., “like” such information). While a number of likes is ostensibly proportional to the social relevance of such information, other factors are frequently left unconsidered. For instance, programmatic scripts are known to be used to repeatedly and automatically assign likes to information, thereby falsely inflating its social relevance. Users may also simply “like” information posted by their close connections regardless of its actual content.
The technology behind computerized social networks often also fails when quantizing connections among users. Often a quantity of connections (friends, contacts, etc.) of a user is displayed, and frequently other users take this quantity to be measure of connectedness, influence, or social reach of the user. As users become more sophisticated, they often discount a user's number of connections by taking into account the failure of the computerized social network to compensate for its inherent weaknesses. The quantity of connections and other metrics become less meaningful. It becomes difficult for anyone to assess the social connectedness of a user with 500 connections versus a user with 50 connections, and the latter user in reality may be more connected.
Status of users is another metric that can assist other users in evaluating authenticity of data pertaining to social connections and interactions. Known types of status include physical status (e.g., online/offline), relational status (e.g., busy, available, etc.), and content-related status (e.g., “contributor”, “new user”, post count, number of friends, number of connections, number of followers, etc.). Many of these could assist in discerning the quality of data presented. However, “gaming” of such systems is common and often status is not indicative of quality. (In this context, gaming means the exploitation or manipulation of rules, systems, or infrastructure to achieve a benefit in a way not intended or condoned by the creator of such.)
The gaming of various computer systems for social connection and interaction can often have real world consequences. Users who have a high status can be afforded more credibility or opportunity inside and outside of the computerized social network. For example, a user who wishes to appear more charitable to obtain employment may need only request connections with charitable users or organizations and post content that has a high chance of being “liked” by such users and organizations. The user may, in reality, not have a charitable nature and may not be a good fit for the job. Further, communications resources may be wasted due to “gamed” status that inaccurately shows that a user is a suitable destination for such communications. Many existing techniques for determining user status are susceptible to gaming or have fundamental flaws that give rise to nonsensical statuses, particularly when comparing the statuses of various users.
The above problems are a result of the computerization of social networks. In physical social networks, people are often naturally skilled at discerning the nature of their cohorts. Often what fosters the lack of authenticity in computerized social networks are the same quantizing and semi-anonymous characteristics that enable their wide reach.